User's Manual User And Installation Guide
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User’s Manual & Installation Guide Streaming Uber Taxi Demand Prediction Liz Aharonian & Ori Ben-Zaken supervisors: Barak Bar-Orion, Yohana Khoury, Yoav Einav, Tal Doron June 2019 General Information USER'S MANUAL & INSTALLATION GUIDE TABLE OF CONTENTS 1.0 1.1 2.0 2.1 GENERAL INFORMATION System Overview INSTALLATION & CONFIGURATION Install InsightEdge [windows] 2.2 Install Docker 2.3 Install Tableaue [windows] 3.0 USING THE APPLICATION 3.1 Running the project 3.2 Download Model File 3.3 Build and Run Docker 3.4 Running Tableaue [windows] 4.0 APPENDIX 4.1 Producer Input Format General Information 1.0 GENERAL INFORMATION Using the Application 1.1 System Overview Our goal is to predict demand per time interval for Uber Taxi Ride, using ML and big data processing tools. The demand parameter is calculated according to time intervals and area, this gives two major advantages to our predicting model: 1. Help the model's users to know which area they should give service. 2. Using a simple function based on the demand to predict and calculate the fare amount. Our architecture is presented in the next schema, details about installation and the way to run the different components are detailed in the next pages. User’s Manual Using the Application 2.0 INSTALLATION & CONFIGURATION Important remark: most of the project runs at Linux environment. In order to make it run in any desired environment and OS, we wrapped it using docker. However, in order to run Tableau BI tool, it is required to have windows environment. Follow the install and running instructions taking into consideration the running environment. Prerequisites: 1. Java Environment 2. Python 3 User’s Manual Using the Application 2.1 Install InsightEdge [windows] Download I9E1 installation zip using the next link: https://gigaspaces-releases-eu.s3.amazonaws.com/insightedge/14.5.0/gigaspaces-insightedge-enterprise14.5.0-m7.zip Get into/ xap-license.txt, change the text inside it to: "tryme". 2.2 Install Docker Install Docker and Docker-Compose from Docker official website: Install Docker: https://docs.docker.com/v17.12/install/ Install Docker Compose: https://docs.docker.com/compose/install/ 2.3 Install Tableaue [windows] Install Tableaue BI application fron Tableaue's website. Get into /insightedge\tools\jdbc\tableau Follow the next instructions detailed in the README.txt file: 1. Run install maven rep of XAP and InsightEdge: /tools/maven/installmavenrep.cmd and /insightedge/tools/maven/insightedge-maven.cmd 2. Run build-jdbc-client.cmd command: ( /insightedge/tools/jdbc/build-jdbc-client.cmd 3. Copy the created insightedge-jdbc-client.jar to C:\Program Files\Tableau\Drivers 1 I9E - InsightEdge User’s Manual Using the Application 3.0 USING THE APPLICATION User’s Manual Using the Application 3.1 Running the project NOTE: as mentioned, docker can be installed on Windows\Mac\Linux. The next demonstration relevant to Linux which requires "sudo" before any docker command if the user is not root. Go into our docker folder at: https://github.com/OriBenZaken/Final_Project_Uber/ Go to: Final_Project_Uber/docker Our Docker contains 6 images: • Three zookeeper servers – runs the zookeeper servers which the Kafka server depends on. • Kafka server. • Kafka producer – responsible to run the Kafka producer. • InsightEdge consumer – responsible to run I9E first, and then the Kafka consumer. 3.2 Download Model File This step is required in order to build docker images of our project later on, and supply them our serialized trained best-model of taxi demand prediction per area and time. Please go to this link: https://drive.google.com/file/d/1bLlpWQCQwM2HInZKLQE46pdXOYwCqRe4/view?usp=sharing Download the model file and locate it in Final_Project_Uber/docker/src directory. 3.3 Build and Run Docker Run the next command to build the local images: ./build-local-images.sh Then, run the docker compose, using the command: sudo docker-compose up -d && sudo docker attach producer The docker compose is responsible to run and create containers of all the existing images we have created, in addition to images which available remotely. The docker compose responsible to run each of them in a certain order, to ensure each image runs only when the images that it is depends on have already been activated. The above command starts all our needed services in detached mode and right after that attaches to the Kafka producer service, which is waiting for input – new ride information. Attach to the Kafka consumer in order to see its output: sudo docker attach consumer User’s Manual Using the Application Next, go to InsightEdge grid (Xap), at the address: http://localhost:8099/ Go to spaces > demo (DB name) > Types, see the table: "model.v1.UberRecord" The table contains 40,000 records of past rides: Enter new ride information in the specified format2: Now, the new entered record is passed to the consumer via Kafka's queue. You can see the output in the consumer window: 2 See the appendix for more details about the input format. User’s Manual Using the Application See the rows number grows at the WebUI: To stop the docker, and close the network created by it press: CTRL C And then enter: sudo docker-compose down 3.4 Running Tableaue [windows] Precondition to run Tableaue: run I9E using the docker compose detailed in the previous stage. Then, follow the next instructions: 1. Run \bin\tableau.exe DConnectPluginsPath= \insightedge\tools\jdbc 5. In Tableau's "To a Server" menu, choose "Gigaspaces InsightEdge". User’s Manual Using the Application 6. In Server field, fill the locator – insert the ip of the linux computer in which you operated the previous stage (stage 3.1) 7. In Space field, write the space name – "demo" 8. All other fields are optional 9. Sign in. Create a new sheet or open the existing sheet we have already created, to do so select: File > Open: Take the Tableaue queries.twb file from: https://github.com/OriBenZaken/Final_Project_Uber/tree/master/tableau/ User’s Manual Using the Application 4.0 APPENDIX User’s Manual Using the Application 4.1 Producer Input Format: As mentioned in the previous section, new ride information need to be inserted into the producer. Here is information about the data types and correct format: Feature: Data type: Notes: latitude DoubleType Latitude where the meter was disengaged. longitude DoubleType Longitude where the meter was disengaged base IntegerType Indicates the order's area: 0 - 'B02512', 1 - 'B02598', 2 - 'B02617', 3 - 'B02682', 4 - 'B02764', 5 - 'B02765', 6 - 'B02835', 7 - 'B02836' weekday IntegerType day month year hour isWeekend IntegerType IntegerType IntegerType IntegerType IntegerType 0 – Sunday 1 – Monday 2 – Tuesday 3 – Wednesday 4 – Thursday 5 – Friday 6 – Saturday Day of date isHoliday IntegerType User’s Manual Four digits format 0 – not weekend 1 – weekend 0 – holiday 1 – not holiday Determined according US holidays.
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